docstr: Apply a 2D adaptive average pooling over an input signal composed of
  several input planes.
  
  Parameters
  ----------
  self
      A 3D or 4D input array. Should have a floating-point data type.
  output_size
      Spatial output size.
  data_format
      "NHWC" or "NCHW". Defaults to "NHWC".
  
  Returns
  -------
      The result of the pooling operation. Will have shape (N, C, S_0, S_1) or
      (C, S_0, S_1), where S = `output_size`
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code: def adaptive_avg_pool2d(
      self: ivy.Array,
      output_size: Union[Sequence[int], int],
      /,
      *,
      data_format: str = "NHWC",
  ) -> ivy.Array:
      """Apply a 2D adaptive average pooling over an input signal composed of
      several input planes.
  
      Parameters
      ----------
      self
          A 3D or 4D input array. Should have a floating-point data type.
      output_size
          Spatial output size.
      data_format
          "NHWC" or "NCHW". Defaults to "NHWC".
  
      Returns
      -------
          The result of the pooling operation. Will have shape (N, C, S_0, S_1) or
          (C, S_0, S_1), where S = `output_size`
      """
      return ivy.adaptive_avg_pool2d(
          self._data,
          output_size,
          data_format=data_format,
      )
  
imports: import abc
  from typing import Optional, Union, Tuple, List, Literal, Sequence, Callable
  import ivy
label_desc: Use image node_id 15 for calling the _ArrayWithLayersExperimental obj's underlying member method code with example usage: obj.adaptive_avg_pool2d() and returns: ivy